- My notebook queries a database for some data -> I run some downstream calculations. Re-querying returns slightly different data, but using cached outputs means I can replicate the work.
- In another notebook, I was trying to replicate my coworkers work where he queried OpenAI a few thousand times. The results may be different when I run it, since OpenAI changed something.
When notebooks are used well, it's in the context of internal data / ML project collaboration. So being able to flash-freeze a cell for your collaborators helps you juggle and pass around notebooks more easily with confidence.
Shipping notebooks directly to production is a whole another set of challenges that I have my own, separate opinions on but that's a different beast entirely.